Five UBC Computer Science papers accepted at NeurIPS 2020
The UBC Computer Science department is celebrating the fact that five of the department members’ papers have been accepted at the 34th annual Neural Information Processing System (NeurIPS) conference. In combination with six other UBC papers accepted from CAIDA members, that makes 11 papers accepted from UBC in total at the biggest, most prestigious machine learning conference of the year.
The event is happening virtually on Dec. 6 – 12.
NeurIPS has had a whopping 9,467 full submissions in total (that’s 38 percent more than for NeurIPS 2019). Of those, a total of 1,903 papers were accepted.
Those UBC Computer Science Department members whose papers have been accepted are as follows (in bold):
Hu Fu and Tao Lin; Learning Utilities and Equilibria in Non-Truthful Auctions
J. Hartford, K. Leyton-Brown, H. Raviv, D. Padnos, S. Lev, B. Lenz; Exemplar Guided Active Learning
Chris Liaw, Tasuku Soma, Nicholas J. A. Harvey; Improved Algorithms for Online Submodular Maximization via First-order Regret Bounds
Vaden Masrani, Frank Wood, Rob Brekelmans, Michael A. Osborne, Vu Nguyen; Gaussian Process Bandit Optimization of the Thermodynamic Variational Objective
Victor Sanches Portella, Joey Zhou, Nicholas J. A. Harvey, Mark Schmidt; Regret Bounds without Lipschitz Continuity: Online Learning with Relative-Lipschitz Losses
G. Weisz, A. Gyorgy, W. Lin, D. Graham, K. Leyton-Brown, C. Szepesvari, B. Lucier; ImpatientCapsAndRuns: Approximately Optimal Algorithm Configuration from an Infinite Pool
With UBC Computer Science’s continued focus on machine learning, injection of funding, awards, government support and industry support, the department is well-poised to support its compounding expansion.
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